Object Detection and Tracking in Real Time Videos

Christian R. Llano, Yuan Ren and Nazrul I. Shaikh
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Christian R. Llano: Department of Industrial Engineering, University of Miami, Coral Gables, USA
Yuan Ren: Department of Industrial Engineering, Shanghai Dianji University, Shanghai Shi, China
Nazrul I. Shaikh: Department of Industrial Engineering, University of Miami, Coral Gables, USA

International Journal of Information Systems in the Service Sector (IJISSS), 2019, vol. 11, issue 2, 1-17

Abstract: Object and human tracking in streaming videos are one of the most challenging problems in vision computing. In this article, we review some relevant machine learning algorithms and techniques for human identification and tracking in videos. We provide details on metrics and methods used in the computer vision literature for monitoring and propose a state-space representation of the object tracking problem. A proof of concept implementation of the state-space based object tracking using particle filters is presented as well. The proposed approach enables tracking objects/humans in a video, including foreground/background separation for object movement detection.

Date: 2019
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